By Topic

Mining Approximative Descriptions of Sets Using Rough Sets

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Simovici, D.A. ; Dept. of Comput. Sci., Univ. of Massachusetts Boston, Boston, MA ; Mimaroglu, S.

Using concepts from rough set theory we investigate the existence of approximative descriptions of collections of objects that can be extracted from in data set, a problem of interest for biologists that need to find succinct descriptions of families of taxonomic units. Our algorithm is based on an anti-monotonicity of borders of object set and makes use of an approach that is, in a certain sense, a dual of the a priori algorithm used in identifying frequent item sets.

Published in:

Multiple-Valued Logic, 2009. ISMVL '09. 39th International Symposium on

Date of Conference:

21-23 May 2009